Metaheuristic algorithms for the hybrid flowshop scheduling problem

Öztop, Hande; Taşgetiren, M. Fatih; Eliiyi, Deniz Türsel; Pan, Quan-Ke

doi:10.1016/j.cor.2019.06.009

Cited by 74 publications

(15 citation statements)

References 45 publications

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“…Khare and Agrawal [30] studied the HFSP to minimize total weighted earliness and tardiness, applying three population-based hybrid metaheuristics to tackle the NP-hard problem. Öztop et al [48] developed an optimization model, four variants of iterated greedy algorithms, and a variable block insertion heuristic for the HFSP to minimize total flow time. Zhang et al [73] introduced a multi-objective optimization model for the hybrid flowshop green scheduling problem (HFGSP) with variable machine processing speeds.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparison of lot streaming division methodologies for multi-objective hybrid flowshop scheduling problem by considering limited waiting time

Yılmaz,

Yeni

2024

JIMO

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In this paper, a multi-objective hybrid flowshop scheduling problem (HFSP) with limited waiting time and machine capability constraints is addressed. Given its importance, the implementation of lot streaming division methodologies with the problem is investigated through a design of experiment (DoE) setting based on real data extracted from a leading tire manufacturer in Gebze, Turkey. By doing so, specific characteristics of the addressed HFSP can be further explored to provide insights into its complexity and suggest recommendations for improving the operational efficiency of such systems resembling it. Based on the problem specifications and constraints, a novel generic multi-objective optimization model with objectives including the makespan, the average flow time, and the total workload imbalance is formulated. Since the studied problem is NP-hard in the strong sense, several algorithms based on the non-dominated sorting genetic algorithm-II (NSGA-II) are proposed according to the division methodologies, i.e., consistent sublots and equal sublots. Since the main aim of this problem is to further analyze the implementation of lot streaming on the HFSP problem, the developed algorithms are compared with each other to gain remarkable insights into the problem. Four different comparison metrics are employed to assess the solution quality of the proposed algorithms in terms of intensification and diversification aspects. Computational results demonstrate that employing the consistent sublot methodology leads to significant improvements in all metrics compared to the equal sublot methodology.

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Section: Literature Reviewmentioning

confidence: 99%

Comparison of lot streaming division methodologies for multi-objective hybrid flowshop scheduling problem by considering limited waiting time

Yılmaz,

Yeni

2024

JIMO

View full text Add to dashboard Cite

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“…However, due to the NP-hardness of HFSP, when the problem size grows, it is difficult for the precise optimization algorithms proposed by many later scholars to find the optimal solution in a reasonable computation time. Therefore, heuristic and metaheuristic algorithms emerged to solve HFSP [14].…”

Section: Related Workmentioning

confidence: 99%

Research on Production Scheduling Technology in Knitting Workshop Based on Improved Genetic Algorithm

et al. 2023

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Production scheduling in a knitting workshop is an important method to improve production efficiency, reduce costs and improve service. In order to achieve a reasonable allocation of parallel machines as well as cooperation between different machines within the workshop, thereby ensuring the optimal scheduling of production plans, this paper proposes a scheduling method using an improved genetic algorithm (IGA) based on tabu search. Firstly, the production scheduling model of a knitting workshop is established. Secondly, an IGA based on the minimum processing time rule, the priority idle machine rule and the production order ranking code is used to optimize the solution. Finally, an experiment platform for knitting workshop production is built to verify the proposed scheduling method. The experimental results show that the proposed IGA based on tabu search performs well in terms of preconvergence speed, global search capability and local search capability. The IGA converges faster than the traditional genetic algorithm by about 25%, reduces the redundancy time of scheduling, meets the production requirements of the knitting intelligent workshop and has a good reference value for promoting the intelligent development of knitting production.

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“…By retrieving the research results, branch-and-bound algorithm is a commonly used and effective method in getting the exact solution of hybrid flow-shop problem [10], [20]- [22]. And, in the aspect of heuristic algorithm, there are many effective algorithms based on iterated greedy idea for hybrid flow-shop problem [23]- [25]. Next, we also take the problem FSFT as an example to compare the effects of DPA (given in this paper), branch-and-bound algorithm (denoted as B&B, based on Lee and Kim [22]) and iterated greedy algorithm (denoted as IG, based on Wang and Wang [24]) on the two-machine hybrid flow-shop problem considered in this paper.…”

Section: B Comparison With Traditional Algorithmsmentioning

confidence: 99%

Dynamic Programming Algorithms for Two-Machine Hybrid Flow-Shop Scheduling With a Given Job Sequence and Deadline

Wei

2020

IEEE Access

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In ''Shared Manufacturing'' environment, orders are processed in a given job sequence which is based on the time of receipt of orders. This paper studies a problem of scheduling two-task jobs in a two-machine hybrid flow-shop subject to a given job sequence which is used in production of electronic circuits under shared manufacturing. Each job has two tasks: the first one is a flexible task, which can be processed on either of the two machines, and the second one is a preassigned task, which can only be processed on the second machine after the first task is finished. Each job has a processing deadline. Three objective functions related to deadlines are considered. The computational complexity of the problem for any of three objective functions is showed to be ordinary NP-hard, a dynamic programming algorithm (DPA) is presented for each case and the time complexity of each algorithm is given. The results of computational experiments show the relationship between the running time of DPA and the parameters, and also show the advantages of DPA in dealing with this problem compared with branch-and-bound algorithm and iterated greedy algorithm. INDEX TERMS Shared manufacturing, hybrid flow shop, dynamic programming algorithm, computational complexity.

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Metaheuristic algorithms for the hybrid flowshop scheduling problem

Cited by 74 publications

References 45 publications

Comparison of lot streaming division methodologies for multi-objective hybrid flowshop scheduling problem by considering limited waiting time

Comparison of lot streaming division methodologies for multi-objective hybrid flowshop scheduling problem by considering limited waiting time

Research on Production Scheduling Technology in Knitting Workshop Based on Improved Genetic Algorithm

Dynamic Programming Algorithms for Two-Machine Hybrid Flow-Shop Scheduling With a Given Job Sequence and Deadline

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